Rationale and Objectives
Reported error rates for initial clinical diagnosis of idiopathic Parkinson’s disease (IPD) against other Parkinson Plus Syndromes (PPS) can reach up to 35%. Reducing this initial error rate is an important research goal. We evaluated the ability of an automated technique, based on structural, cross-sectional T1-weighted (T1w) magnetic resonance imaging, to perform differential classification of IPD patients versus those with either progressive supranuclear palsy (PSP) or multiple systems atrophy (MSA).
Materials and Methods
A total of 181 subjects were included in this retrospective study: 149 healthy controls, 16 IPD patients, and 16 patients diagnosed with either probable PSP ( n = 8) or MSA ( n = 8). Cross-sectional T1w magnetic resonance imagers were acquired and subsequently corrected, scaled, resampled, and aligned within a common referential space. Tissue composition and deformation features in the hindbrain region were then automatically extracted. Classification of patients was performed using a support vector machine with least-squares optimization within a multidimensional composition/deformation feature space built from the healthy subjects’ data. Leave-one-out classification was used to avoid over-determination.
Results
There were no age difference between groups. The automated system obtained 91% accuracy (agreement with long-term clinical follow-up), 88% specificity, and 93% sensitivity.
Conclusion
These results demonstrate that a classification approach based on quantitative parameters of three-dimensional hindbrain morphology extracted automatically from T1w magnetic resonance imaging has the potential to assist in the differential diagnosis of IPD versus PSP and MSA with high accuracy, therefore reducing the initial clinical error rate.
Multiple systems atrophy (MSA) and progressive supranuclear palsy (PSP) represent, when combined, the second most prevalent cause of degenerative parkinsonian syndromes, after idiopathic Parkinsons’ disease (IPD) ( ). Classified as Parkinsonian Plus Syndromes (PPS), these diseases primarily affect middle-aged adults with a maximum incidence at 55 years of age and a male/female ratio of 1.5 to 1 ( ).
It is difficult to differentiate PSP and MSA clinically in early stages from IPD. Clinical diagnosis is established on the basis of criteria from Gilman et al. ( ) for MSA and from Litvan et al. ( ) for PSP. Patients with MSA exhibit autonomic failure and cerebellar and pyramidal involvement. Clinical symptoms of PSP include oculomotor abnormalities, early falls, pyramidal symptoms, and frontal lobe dysfunction. Early diagnosis is crucial, as dissimilar therapy choices must be pursued depending on status. The situation is worsened by the fact that the disease course in PPS is more rapid than IPD, with lower median survival (6 vs. 18 years in IPD).
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Figure 1
Mesencephalon atrophy in probable progressive supranuclear palsy (PSP) on sagittal T1-weighted images. (a) Absent, (b) moderate, and (c) Severe.
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Figure 2
Pontine atrophy, cerebellar atrophy, and enlargement of the fourth ventricle in probable multiple systems atrophy (MSA) on sagittal T1-weighted images. (a) Absent, (b) moderate, and (c) severe.
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Figure 3
Prior to feature extraction, the original image ( top left ) is globally and locally aligned with the target volume of interest (VOI) ( bottom left ); the intensity is then corrected, scaled, and clamped. The resulting image ( top right ) is used as a measure of tissue composition. The determinant of the nonlinear registration field mapping the tissue composition image to the target image is then computed as a measure of tissue deformations. When the change is near zero in the neighborhood of x (in light blue/green ) the deformation is incompressible and there is no volume change. However, if the determinant is positive (towards yellow/red ), the volume increases, whereas when negative (towards dark blue ), the volume decreases after the deformation. The red arrows show corresponding areas of mesencephalon and cerebellar atrophy in this particular patient.
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Figure 4
Views through the common target image and the volume of interest (VOI) for this study. The target is a high-contrast, high-resolution average of 27 T1-weighted magnetic resonance imaging scans of the same subject ( ). The VOI measures n = 90 × 90 × 50 = 405,000 voxels and captures structures (eg, pons, mesencephalon) irrespective of normal interindividual variability.
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Materials and methods
Ethics
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Study Type
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Subjects
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Clinical Diagnosis
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Image Data
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Image Processing
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Automated Classification and Statistical Analysis
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Results
Demographics
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Group-level Distributions
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Automated Computer Classification
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Discussion
Clinical Considerations
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Methodologic Considerations
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Study Limitations
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Conclusion
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Acknowledgments
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